Overview

Brought to you by YData

Dataset statistics

Number of variables24
Number of observations1167947
Missing cells7284116
Missing cells (%)26.0%
Duplicate rows348
Duplicate rows (%)< 0.1%
Total size in memory206.1 MiB
Average record size in memory185.0 B

Variable types

Categorical8
Text5
Numeric6
DateTime1
Boolean1
URL3

Dataset

DescriptionEDA of TMDB Movie Dataset. Dataset Source: Asaniczka, and themoviedb.org. (2025). Full TMDB Movies Dataset 2024 (1M Movies) [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/10601279
URLhttps://github.com/ekaterinaleks/RAG
Copyright(c) ekaterinaleks 2025

Variable descriptions

idUnique identifier for each movie
titleTitle of the movie
vote_averageAverage vote or rating given by viewers
vote_countTotal count of votes received for the movie
statusThe status of the movie (e.g., Released, Rumored, Post Production, etc.)
release_dateDate when the movie was released
revenueTotal revenue generated by the movie
runtimeDuration of the movie in minutes
adultIndicates if the movie is suitable only for adult audiences
backdrop_pathURL of the backdrop image for the movie
budgetBudget allocated for the movie
homepageOfficial homepage URL of the movie
imdb_idIMDb ID of the movie
original_languageOriginal language in which the movie was produced
original_titleOriginal title of the movie
overviewBrief description or summary of the movie
popularityPopularity score of the movie
poster_pathURL of the movie poster image
taglineCatchphrase or memorable line associated with the movie
genresList of genres the movie belongs to
production_companiesList of production companies involved in the movie
production_countriesList of countries involved in the movie production
spoken_languagesList of languages spoken in the movie
keywordsKeywords associated with the movie

Alerts

Dataset has 348 (< 0.1%) duplicate rowsDuplicates
id has a high cardinality: 1167129 distinct values High cardinality
imdb_id has a high cardinality: 608703 distinct values High cardinality
original_language has a high cardinality: 174 distinct values High cardinality
genres has a high cardinality: 13507 distinct values High cardinality
production_companies has a high cardinality: 209322 distinct values High cardinality
production_countries has a high cardinality: 10166 distinct values High cardinality
spoken_languages has a high cardinality: 7106 distinct values High cardinality
status is highly imbalanced (92.1%) Imbalance
adult is highly imbalanced (54.7%) Imbalance
original_language is highly imbalanced (57.9%) Imbalance
genres is highly imbalanced (55.2%) Imbalance
production_countries is highly imbalanced (59.8%) Imbalance
spoken_languages is highly imbalanced (63.1%) Imbalance
release_date has 200396 (17.2%) missing values Missing
backdrop_path has 860158 (73.6%) missing values Missing
homepage has 1044970 (89.5%) missing values Missing
imdb_id has 557882 (47.8%) missing values Missing
overview has 241564 (20.7%) missing values Missing
poster_path has 374563 (32.1%) missing values Missing
tagline has 1004366 (86.0%) missing values Missing
genres has 473732 (40.6%) missing values Missing
production_companies has 643803 (55.1%) missing values Missing
production_countries has 523518 (44.8%) missing values Missing
spoken_languages has 503846 (43.1%) missing values Missing
keywords has 855292 (73.2%) missing values Missing
vote_count is highly skewed (γ1 = 41.5415313) Skewed
revenue is highly skewed (γ1 = 72.23530235) Skewed
runtime is highly skewed (γ1 = 34.44181118) Skewed
budget is highly skewed (γ1 = 52.50859104) Skewed
popularity is highly skewed (γ1 = 175.761174) Skewed
id is uniformly distributed Uniform
imdb_id is uniformly distributed Uniform
vote_average has 816876 (69.9%) zeros Zeros
vote_count has 816638 (69.9%) zeros Zeros
revenue has 1146743 (98.2%) zeros Zeros
runtime has 327120 (28.0%) zeros Zeros
budget has 1106990 (94.8%) zeros Zeros
popularity has 143909 (12.3%) zeros Zeros

Reproduction

Analysis started2025-02-02 16:25:20.184274
Analysis finished2025-02-02 16:28:01.648205
Duration2 minutes and 41.46 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

id
Categorical

High cardinality  Uniform 

Unique identifier for each movie

Distinct1167129
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size8.9 MiB
1219302
 
4
1214995
 
4
1265968
 
4
1268961
 
4
1200891
 
4
Other values (1167124)
1167927 

Length

Max length7
Median length6
Mean length6.2711484
Min length1

Unique

Unique1166655 ?
Unique (%)99.9%

Sample

1st row27205
2nd row157336
3rd row155
4th row19995
5th row24428

Common Values

ValueCountFrequency (%)
1219302 4
 
< 0.1%
1214995 4
 
< 0.1%
1265968 4
 
< 0.1%
1268961 4
 
< 0.1%
1200891 4
 
< 0.1%
1258162 4
 
< 0.1%
1210786 4
 
< 0.1%
1225689 4
 
< 0.1%
1262773 4
 
< 0.1%
1265043 4
 
< 0.1%
Other values (1167119) 1167907
> 99.9%

Length

2025-02-02T17:28:01.936076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1219302 4
 
< 0.1%
1209122 4
 
< 0.1%
1222224 4
 
< 0.1%
1257695 4
 
< 0.1%
1216162 4
 
< 0.1%
1263252 4
 
< 0.1%
1219760 4
 
< 0.1%
1252754 4
 
< 0.1%
1213633 4
 
< 0.1%
1264514 4
 
< 0.1%
Other values (1167119) 1167907
> 99.9%

title
Text

Title of the movie

Distinct1000702
Distinct (%)85.7%
Missing13
Missing (%)< 0.1%
Memory size8.9 MiB
2025-02-02T17:28:04.573577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length324
Median length247
Mean length19.899456
Min length1

Unique

Unique937588 ?
Unique (%)80.3%

Sample

1st rowInception
2nd rowInterstellar
3rd rowThe Dark Knight
4th rowAvatar
5th rowThe Avengers
ValueCountFrequency (%)
68493
 
2.4%
2 19686
 
0.7%
live 14525
 
0.5%
love 14392
 
0.5%
3 10032
 
0.4%
night 7995
 
0.3%
life 7994
 
0.3%
story 7993
 
0.3%
big 6609
 
0.2%
world 6583
 
0.2%
Other values (393450) 2638665
94.1%
2025-02-02T17:28:06.030213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

vote_average
Real number (ℝ)

Zeros 

Average vote or rating given by viewers

Distinct5024
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.83587
Minimum0
Maximum10
Zeros816876
Zeros (%)69.9%
Negative0
Negative (%)0.0%
Memory size8.9 MiB
2025-02-02T17:28:06.282586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile8
Maximum10
Range10
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.0015556
Coefficient of variation (CV)1.6349499
Kurtosis0.021203743
Mean1.83587
Median Absolute Deviation (MAD)0
Skewness1.2477299
Sum2144198.9
Variance9.0093357
MonotonicityNot monotonic
2025-02-02T17:28:06.540728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 816876
69.9%
6 30673
 
2.6%
5 29910
 
2.6%
10 25415
 
2.2%
7 24356
 
2.1%
8 19994
 
1.7%
4 11805
 
1.0%
2 9644
 
0.8%
5.5 8737
 
0.7%
6.5 8636
 
0.7%
Other values (5014) 181901
 
15.6%
ValueCountFrequency (%)
0 816876
69.9%
0.5 378
 
< 0.1%
0.75 1
 
< 0.1%
0.8 106
 
< 0.1%
0.875 1
 
< 0.1%
0.9 2
 
< 0.1%
1 6534
 
0.6%
1.1 5
 
< 0.1%
1.167 3
 
< 0.1%
1.179 1
 
< 0.1%
ValueCountFrequency (%)
10 25415
2.2%
9.98 1
 
< 0.1%
9.9 9
 
< 0.1%
9.875 1
 
< 0.1%
9.872 1
 
< 0.1%
9.833 6
 
< 0.1%
9.8 121
 
< 0.1%
9.769 1
 
< 0.1%
9.763 1
 
< 0.1%
9.75 22
 
< 0.1%

vote_count
Real number (ℝ)

Skewed  Zeros 

Total count of votes received for the movie

Distinct3598
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.36544
Minimum0
Maximum34495
Zeros816638
Zeros (%)69.9%
Negative0
Negative (%)0.0%
Memory size8.9 MiB
2025-02-02T17:28:06.803222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile15
Maximum34495
Range34495
Interquartile range (IQR)1

Descriptive statistics

Standard deviation314.22717
Coefficient of variation (CV)17.1097
Kurtosis2361.4737
Mean18.36544
Median Absolute Deviation (MAD)0
Skewness41.541531
Sum21449861
Variance98738.716
MonotonicityDecreasing
2025-02-02T17:28:07.088684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 816638
69.9%
1 126656
 
10.8%
2 49219
 
4.2%
3 28741
 
2.5%
4 20841
 
1.8%
5 14940
 
1.3%
6 11098
 
1.0%
7 8548
 
0.7%
8 6765
 
0.6%
9 5650
 
0.5%
Other values (3588) 78851
 
6.8%
ValueCountFrequency (%)
0 816638
69.9%
1 126656
 
10.8%
2 49219
 
4.2%
3 28741
 
2.5%
4 20841
 
1.8%
5 14940
 
1.3%
6 11098
 
1.0%
7 8548
 
0.7%
8 6765
 
0.6%
9 5650
 
0.5%
ValueCountFrequency (%)
34495 1
< 0.1%
32571 1
< 0.1%
30619 1
< 0.1%
29815 1
< 0.1%
29166 1
< 0.1%
28894 1
< 0.1%
27713 1
< 0.1%
27238 1
< 0.1%
26638 1
< 0.1%
25893 1
< 0.1%

status
Categorical

Imbalance 

The status of the movie (e.g., Released, Rumored, Post Production, etc.)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.9 MiB
Released
1139804 
In Production
 
11398
Post Production
 
8769
Planned
 
7280
Rumored
 
389

Length

Max length15
Median length8
Mean length8.0947851
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 1139804
97.6%
In Production 11398
 
1.0%
Post Production 8769
 
0.8%
Planned 7280
 
0.6%
Rumored 389
 
< 0.1%
Canceled 307
 
< 0.1%

Length

2025-02-02T17:28:07.315894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-02T17:28:07.465257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
released 1139804
96.9%
production 20167
 
1.7%
post 8769
 
0.7%
planned 7280
 
0.6%
rumored 389
 
< 0.1%
canceled 307
 
< 0.1%

release_date
Date

Missing 

Date when the movie was released

Distinct42850
Distinct (%)4.4%
Missing200396
Missing (%)17.2%
Memory size8.9 MiB
Minimum1800-01-01 00:00:00
Maximum2099-11-18 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-02T17:28:07.659736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:28:07.920329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

revenue
Real number (ℝ)

Skewed  Zeros 

Total revenue generated by the movie

Distinct14348
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean686886.16
Minimum-12
Maximum5 × 109
Zeros1146743
Zeros (%)98.2%
Negative1
Negative (%)< 0.1%
Memory size8.9 MiB
2025-02-02T17:28:08.181537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-12
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5 × 109
Range5 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18501768
Coefficient of variation (CV)26.935712
Kurtosis9726.1226
Mean686886.16
Median Absolute Deviation (MAD)0
Skewness72.235302
Sum8.0224663 × 1011
Variance3.4231541 × 1014
MonotonicityNot monotonic
2025-02-02T17:28:08.432366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1146743
98.2%
1 452
 
< 0.1%
100 452
 
< 0.1%
10 255
 
< 0.1%
1000 229
 
< 0.1%
10000 172
 
< 0.1%
100000 167
 
< 0.1%
500 159
 
< 0.1%
2 143
 
< 0.1%
5 136
 
< 0.1%
Other values (14338) 19039
 
1.6%
ValueCountFrequency (%)
-12 1
 
< 0.1%
0 1146743
98.2%
1 452
 
< 0.1%
2 143
 
< 0.1%
3 69
 
< 0.1%
4 40
 
< 0.1%
5 136
 
< 0.1%
6 43
 
< 0.1%
7 29
 
< 0.1%
8 26
 
< 0.1%
ValueCountFrequency (%)
4999999999 1
< 0.1%
3000000000 2
< 0.1%
2930000000 1
< 0.1%
2923706026 1
< 0.1%
2800000000 1
< 0.1%
2320250281 1
< 0.1%
2264162353 1
< 0.1%
2068223624 1
< 0.1%
2052415039 1
< 0.1%
2000000000 1
< 0.1%

runtime
Real number (ℝ)

Skewed  Zeros 

Duration of the movie in minutes

Distinct763
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.294949
Minimum-28
Maximum14400
Zeros327120
Zeros (%)28.0%
Negative1
Negative (%)< 0.1%
Memory size8.9 MiB
2025-02-02T17:28:08.650819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-28
5-th percentile0
Q10
median21
Q388
95-th percentile135
Maximum14400
Range14428
Interquartile range (IQR)88

Descriptive statistics

Standard deviation61.603358
Coefficient of variation (CV)1.3025357
Kurtosis6490.105
Mean47.294949
Median Absolute Deviation (MAD)21
Skewness34.441811
Sum55237994
Variance3794.9737
MonotonicityNot monotonic
2025-02-02T17:28:08.857433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 327120
28.0%
90 30459
 
2.6%
10 18397
 
1.6%
5 17816
 
1.5%
3 17353
 
1.5%
7 16728
 
1.4%
6 16522
 
1.4%
4 15731
 
1.3%
15 14914
 
1.3%
8 14692
 
1.3%
Other values (753) 678215
58.1%
ValueCountFrequency (%)
-28 1
 
< 0.1%
0 327120
28.0%
1 11088
 
0.9%
2 11943
 
1.0%
3 17353
 
1.5%
4 15731
 
1.3%
5 17816
 
1.5%
6 16522
 
1.4%
7 16728
 
1.4%
8 14692
 
1.3%
ValueCountFrequency (%)
14400 1
< 0.1%
13319 1
< 0.1%
12480 1
< 0.1%
9000 1
< 0.1%
7200 1
< 0.1%
5700 1
< 0.1%
5220 1
< 0.1%
4320 1
< 0.1%
3720 1
< 0.1%
2880 1
< 0.1%

adult
Boolean

Imbalance 

Indicates if the movie is suitable only for adult audiences

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
False
1057012 
True
110935 
ValueCountFrequency (%)
False 1057012
90.5%
True 110935
 
9.5%
2025-02-02T17:28:09.016812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

backdrop_path
URL

Missing 

URL of the backdrop image for the movie

Distinct305212
Distinct (%)99.2%
Missing860158
Missing (%)73.6%
Memory size8.9 MiB
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg
 
157
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg
 
66
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg
 
47
/60t9ckELUGyinDQNDULFDq2i7u7.jpg
 
44
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg
 
43
Other values (305207)
307432 
(Missing)
860158 
ValueCountFrequency (%)
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg 157
 
< 0.1%
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg 66
 
< 0.1%
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg 47
 
< 0.1%
/60t9ckELUGyinDQNDULFDq2i7u7.jpg 44
 
< 0.1%
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg 43
 
< 0.1%
/vG0YKrbBQcDSFZYDE1zIqGhqpmc.jpg 38
 
< 0.1%
/dEJ9tgpv8Ly9VeH2TW1wAm4gBbY.jpg 31
 
< 0.1%
/3wkhoahQHZRcl7OaKymA2lGPSVg.jpg 27
 
< 0.1%
/rUcFNAwnTFiKtijDlDp8Ukgz48j.jpg 25
 
< 0.1%
/49qOx6QBOa2p7dKS16AIrLgX29e.jpg 24
 
< 0.1%
Other values (305202) 307287
 
26.3%
(Missing) 860158
73.6%
ValueCountFrequency (%)
307789
 
26.4%
(Missing) 860158
73.6%
ValueCountFrequency (%)
307789
 
26.4%
(Missing) 860158
73.6%
ValueCountFrequency (%)
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg 157
 
< 0.1%
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg 66
 
< 0.1%
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg 47
 
< 0.1%
/60t9ckELUGyinDQNDULFDq2i7u7.jpg 44
 
< 0.1%
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg 43
 
< 0.1%
/vG0YKrbBQcDSFZYDE1zIqGhqpmc.jpg 38
 
< 0.1%
/dEJ9tgpv8Ly9VeH2TW1wAm4gBbY.jpg 31
 
< 0.1%
/3wkhoahQHZRcl7OaKymA2lGPSVg.jpg 27
 
< 0.1%
/rUcFNAwnTFiKtijDlDp8Ukgz48j.jpg 25
 
< 0.1%
/49qOx6QBOa2p7dKS16AIrLgX29e.jpg 24
 
< 0.1%
Other values (305202) 307287
 
26.3%
(Missing) 860158
73.6%
ValueCountFrequency (%)
307789
 
26.4%
(Missing) 860158
73.6%
ValueCountFrequency (%)
307789
 
26.4%
(Missing) 860158
73.6%

budget
Real number (ℝ)

Skewed  Zeros 

Budget allocated for the movie

Distinct5811
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean264891.05
Minimum0
Maximum1 × 109
Zeros1106990
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size8.9 MiB
2025-02-02T17:28:09.208780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum1 × 109
Range1 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5085605.1
Coefficient of variation (CV)19.198856
Kurtosis5433.7432
Mean264891.05
Median Absolute Deviation (MAD)0
Skewness52.508591
Sum3.0937871 × 1011
Variance2.5863379 × 1013
MonotonicityNot monotonic
2025-02-02T17:28:09.438623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1106990
94.8%
100 2106
 
0.2%
1000 1931
 
0.2%
500 1636
 
0.1%
10000 1607
 
0.1%
5000 1582
 
0.1%
2000 1264
 
0.1%
200 1115
 
0.1%
50 1075
 
0.1%
10 1074
 
0.1%
Other values (5801) 47567
 
4.1%
ValueCountFrequency (%)
0 1106990
94.8%
1 950
 
0.1%
2 393
 
< 0.1%
3 256
 
< 0.1%
4 157
 
< 0.1%
5 624
 
0.1%
6 125
 
< 0.1%
7 111
 
< 0.1%
8 106
 
< 0.1%
9 56
 
< 0.1%
ValueCountFrequency (%)
999999999 1
 
< 0.1%
900000000 1
 
< 0.1%
888000000 1
 
< 0.1%
800000000 1
 
< 0.1%
645654654 1
 
< 0.1%
600000000 2
< 0.1%
540000000 1
 
< 0.1%
500000000 3
< 0.1%
470000000 1
 
< 0.1%
460000000 1
 
< 0.1%

homepage
URL

Missing 

Official homepage URL of the movie

Distinct115402
Distinct (%)93.8%
Missing1044970
Missing (%)89.5%
Memory size8.9 MiB
https://animation.geidai.ac.jp
 
147
http://www.eldoradofilms.com
 
74
https://www.yamidouga.com/
 
63
https://uaebabes.com
 
57
http://www.ufc.com
 
52
Other values (115397)
122584 
(Missing)
1044970 
ValueCountFrequency (%)
https://animation.geidai.ac.jp 147
 
< 0.1%
http://www.eldoradofilms.com 74
 
< 0.1%
https://www.yamidouga.com/ 63
 
< 0.1%
https://uaebabes.com 57
 
< 0.1%
http://www.ufc.com 52
 
< 0.1%
https://www.youtube.com/ 52
 
< 0.1%
https://pinoyflix.to/ 50
 
< 0.1%
http://www.battlefieldhistory.tv 49
 
< 0.1%
http://www.demand-progress.com 44
 
< 0.1%
https://parallaximag.gr/to-5o-panorama-tainion-tou-tmimatos-kinimatografou-tou-apth-erchetai-sto-cinobo-114082 40
 
< 0.1%
Other values (115392) 122349
 
10.5%
(Missing) 1044970
89.5%
ValueCountFrequency (%)
https 75483
 
6.5%
http 47475
 
4.1%
19
 
< 0.1%
(Missing) 1044970
89.5%
ValueCountFrequency (%)
www.youtube.com 9312
 
0.8%
vimeo.com 3576
 
0.3%
www.bbc.co.uk 2032
 
0.2%
www.netflix.com 1598
 
0.1%
www.nikkatsu.com 1555
 
0.1%
youtu.be 1176
 
0.1%
filmfreeway.com 1075
 
0.1%
www.facebook.com 1003
 
0.1%
www.nfb.ca 790
 
0.1%
www.pbs.org 674
 
0.1%
Other values (55090) 100186
 
8.6%
(Missing) 1044970
89.5%
ValueCountFrequency (%)
/ 25250
 
2.2%
13861
 
1.2%
/watch 7819
 
0.7%
/index.php 275
 
< 0.1%
/film/info/ 239
 
< 0.1%
/video 182
 
< 0.1%
/index.html 156
 
< 0.1%
/en/ 155
 
< 0.1%
/films 131
 
< 0.1%
/FAMS_ipac/cclib/search/showBib.jsp 118
 
< 0.1%
Other values (69224) 74791
 
6.4%
(Missing) 1044970
89.5%
ValueCountFrequency (%)
110002
 
9.4%
lang=en 125
 
< 0.1%
share=copy 93
 
< 0.1%
v=7516fd43adaa 59
 
< 0.1%
showCards=1 45
 
< 0.1%
fref=ts 26
 
< 0.1%
locale=en 23
 
< 0.1%
ref_=ext_shr_lnk 21
 
< 0.1%
partner_id=24903038 19
 
< 0.1%
fbclid=IwAR1jSDQd2twJPGTd2bedseZKv17nM7KypVCRgPBxPCc8vpx__L_QzyLrxFA 17
 
< 0.1%
Other values (12061) 12547
 
1.1%
(Missing) 1044970
89.5%
ValueCountFrequency (%)
121688
 
10.4%
/ 130
 
< 0.1%
/extra 31
 
< 0.1%
story 27
 
< 0.1%
1 18
 
< 0.1%
overview 12
 
< 0.1%
home 11
 
< 0.1%
Review 10
 
< 0.1%
/fight 10
 
< 0.1%
WSU 9
 
< 0.1%
Other values (927) 1031
 
0.1%
(Missing) 1044970
89.5%

imdb_id
Categorical

High cardinality  Missing  Uniform 

IMDb ID of the movie

Distinct608703
Distinct (%)99.8%
Missing557882
Missing (%)47.8%
Memory size8.9 MiB
tt32094375
 
68
tt13904644
 
28
tt26900526
 
20
tt8657468
 
16
tt23810972
 
15
Other values (608698)
609918 

Length

Max length10
Median length9
Mean length9.1961447
Min length8

Unique

Unique607839 ?
Unique (%)99.6%

Sample

1st rowtt1375666
2nd rowtt0816692
3rd rowtt0468569
4th rowtt0499549
5th rowtt0848228

Common Values

ValueCountFrequency (%)
tt32094375 68
 
< 0.1%
tt13904644 28
 
< 0.1%
tt26900526 20
 
< 0.1%
tt8657468 16
 
< 0.1%
tt23810972 15
 
< 0.1%
tt5719786 13
 
< 0.1%
tt27430909 12
 
< 0.1%
tt29703523 11
 
< 0.1%
tt27048168 10
 
< 0.1%
tt10980608 10
 
< 0.1%
Other values (608693) 609862
52.2%
(Missing) 557882
47.8%

Length

2025-02-02T17:28:09.661646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt32094375 68
 
< 0.1%
tt13904644 28
 
< 0.1%
tt26900526 20
 
< 0.1%
tt8657468 16
 
< 0.1%
tt23810972 15
 
< 0.1%
tt5719786 13
 
< 0.1%
tt27430909 12
 
< 0.1%
tt29703523 11
 
< 0.1%
tt27048168 10
 
< 0.1%
tt10980608 10
 
< 0.1%
Other values (608693) 609862
> 99.9%

original_language
Categorical

High cardinality  Imbalance 

Original language in which the movie was produced

Distinct174
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.9 MiB
en
631173 
fr
68368 
es
 
59270
de
 
55131
ja
 
50732
Other values (169)
303273 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
en 631173
54.0%
fr 68368
 
5.9%
es 59270
 
5.1%
de 55131
 
4.7%
ja 50732
 
4.3%
zh 39950
 
3.4%
pt 34610
 
3.0%
it 24499
 
2.1%
ru 23989
 
2.1%
ko 13624
 
1.2%
Other values (164) 166601
 
14.3%

Length

2025-02-02T17:28:09.842426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fr 68368
25.6%
zh 39950
15.0%
pt 34610
13.0%
ru 23989
 
9.0%
cs 11045
 
4.1%
nl 9222
 
3.5%
sv 8767
 
3.3%
tr 8018
 
3.0%
pl 7293
 
2.7%
tl 6637
 
2.5%
Other values (96) 49141
18.4%

original_title
Text

Original title of the movie

Distinct1034909
Distinct (%)88.6%
Missing13
Missing (%)< 0.1%
Memory size8.9 MiB
2025-02-02T17:28:11.768543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length250
Median length211
Mean length18.858123
Min length1

Unique

Unique975725 ?
Unique (%)83.5%

Sample

1st rowInception
2nd rowInterstellar
3rd rowThe Dark Knight
4th rowAvatar
5th rowThe Avengers
ValueCountFrequency (%)
67711
 
2.5%
2 18363
 
0.7%
live 13753
 
0.5%
3 9393
 
0.3%
love 9005
 
0.3%
story 6269
 
0.2%
4 5894
 
0.2%
1 5735
 
0.2%
night 5679
 
0.2%
life 5572
 
0.2%
Other values (528342) 2569928
94.6%
2025-02-02T17:28:13.136040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

overview
Text

Missing 

Brief description or summary of the movie

Distinct899849
Distinct (%)97.1%
Missing241564
Missing (%)20.7%
Memory size8.9 MiB
2025-02-02T17:28:25.335740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1000
Median length804
Mean length269.07154
Min length1

Unique

Unique891635 ?
Unique (%)96.2%

Sample

1st rowCobb, a skilled thief who commits corporate espionage by infiltrating the subconscious of his targets is offered a chance to regain his old life as payment for a task considered to be impossible: "inception", the implantation of another person's idea into a target's subconscious.
2nd rowThe adventures of a group of explorers who make use of a newly discovered wormhole to surpass the limitations on human space travel and conquer the vast distances involved in an interstellar voyage.
3rd rowBatman raises the stakes in his war on crime. With the help of Lt. Jim Gordon and District Attorney Harvey Dent, Batman sets out to dismantle the remaining criminal organizations that plague the streets. The partnership proves to be effective, but they soon find themselves prey to a reign of chaos unleashed by a rising criminal mastermind known to the terrified citizens of Gotham as the Joker.
4th rowIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.
5th rowWhen an unexpected enemy emerges and threatens global safety and security, Nick Fury, director of the international peacekeeping agency known as S.H.I.E.L.D., finds himself in need of a team to pull the world back from the brink of disaster. Spanning the globe, a daring recruitment effort begins!
ValueCountFrequency (%)
film 154890
 
0.7%
125066
 
0.6%
life 114398
 
0.5%
young 96598
 
0.5%
love 80665
 
0.4%
world 74523
 
0.3%
story 73221
 
0.3%
time 69949
 
0.3%
family 57081
 
0.3%
years 53201
 
0.2%
Other values (656206) 20545461
95.8%
2025-02-02T17:28:27.155019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

popularity
Real number (ℝ)

Skewed  Zeros 

Popularity score of the movie

Distinct19888
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2143889
Minimum0
Maximum2994.357
Zeros143909
Zeros (%)12.3%
Negative0
Negative (%)0.0%
Memory size8.9 MiB
2025-02-02T17:28:27.312400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median0.6
Q30.874
95-th percentile3.185
Maximum2994.357
Range2994.357
Interquartile range (IQR)0.274

Descriptive statistics

Standard deviation7.4862089
Coefficient of variation (CV)6.1645891
Kurtosis50644.927
Mean1.2143889
Median Absolute Deviation (MAD)0
Skewness175.76117
Sum1418341.9
Variance56.043324
MonotonicityNot monotonic
2025-02-02T17:28:27.520167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 611899
52.4%
0 143909
 
12.3%
1.4 31267
 
2.7%
0.84 9171
 
0.8%
0.65 4155
 
0.4%
0.841 3666
 
0.3%
0.9 2252
 
0.2%
0.651 1902
 
0.2%
1.09 1719
 
0.1%
0.621 1558
 
0.1%
Other values (19878) 356449
30.5%
ValueCountFrequency (%)
0 143909
 
12.3%
0.36 7
 
< 0.1%
0.363 1
 
< 0.1%
0.59 2
 
< 0.1%
0.6 611899
52.4%
0.601 977
 
0.1%
0.602 830
 
0.1%
0.603 633
 
0.1%
0.604 527
 
< 0.1%
0.605 505
 
< 0.1%
ValueCountFrequency (%)
2994.357 1
< 0.1%
2680.593 1
< 0.1%
2020.286 1
< 0.1%
1692.778 1
< 0.1%
1567.273 1
< 0.1%
1547.22 1
< 0.1%
1458.514 1
< 0.1%
1175.267 1
< 0.1%
1111.036 1
< 0.1%
1069.34 1
< 0.1%

poster_path
URL

Missing 

URL of the movie poster image

Distinct788737
Distinct (%)99.4%
Missing374563
Missing (%)32.1%
Memory size8.9 MiB
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg
 
54
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg
 
54
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg
 
48
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg
 
45
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg
 
41
Other values (788732)
793142 
(Missing)
374563 
ValueCountFrequency (%)
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg 54
 
< 0.1%
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg 54
 
< 0.1%
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg 48
 
< 0.1%
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg 45
 
< 0.1%
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg 41
 
< 0.1%
/nelvhFPqwYhAw8UFF81sDpFZSlD.jpg 39
 
< 0.1%
/9nQJc8M6u7J4LISv44Y9dMbhQTg.jpg 37
 
< 0.1%
/28vbk6H0CeVmT4aJRADatqCFXmR.jpg 36
 
< 0.1%
/AuLuyBTQs0ecbQXnSHwcKRnn6Qo.jpg 34
 
< 0.1%
/44XDqrWNPiBkIT1ixdtLX23LKlQ.jpg 33
 
< 0.1%
Other values (788727) 792963
67.9%
(Missing) 374563
32.1%
ValueCountFrequency (%)
793384
67.9%
(Missing) 374563
32.1%
ValueCountFrequency (%)
793384
67.9%
(Missing) 374563
32.1%
ValueCountFrequency (%)
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg 54
 
< 0.1%
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg 54
 
< 0.1%
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg 48
 
< 0.1%
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg 45
 
< 0.1%
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg 41
 
< 0.1%
/nelvhFPqwYhAw8UFF81sDpFZSlD.jpg 39
 
< 0.1%
/9nQJc8M6u7J4LISv44Y9dMbhQTg.jpg 37
 
< 0.1%
/28vbk6H0CeVmT4aJRADatqCFXmR.jpg 36
 
< 0.1%
/AuLuyBTQs0ecbQXnSHwcKRnn6Qo.jpg 34
 
< 0.1%
/44XDqrWNPiBkIT1ixdtLX23LKlQ.jpg 33
 
< 0.1%
Other values (788727) 792963
67.9%
(Missing) 374563
32.1%
ValueCountFrequency (%)
793384
67.9%
(Missing) 374563
32.1%
ValueCountFrequency (%)
793384
67.9%
(Missing) 374563
32.1%

tagline
Text

Missing 

Catchphrase or memorable line associated with the movie

Distinct157115
Distinct (%)96.0%
Missing1004366
Missing (%)86.0%
Memory size8.9 MiB
2025-02-02T17:28:28.417301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length256
Median length231
Mean length45.01491
Min length1

Unique

Unique154222 ?
Unique (%)94.3%

Sample

1st rowYour mind is the scene of the crime.
2nd rowMankind was born on Earth. It was never meant to die here.
3rd rowWelcome to a world without rules.
4th rowEnter the world of Pandora.
5th rowSome assembly required.
ValueCountFrequency (%)
8039
 
1.3%
love 7917
 
1.2%
story 5762
 
0.9%
life 5121
 
0.8%
world 3692
 
0.6%
film 3481
 
0.5%
time 3445
 
0.5%
live 2167
 
0.3%
back 2064
 
0.3%
family 1828
 
0.3%
Other values (67348) 591749
93.1%
2025-02-02T17:28:29.309455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genres
Categorical

High cardinality  Imbalance  Missing 

List of genres the movie belongs to

Distinct13507
Distinct (%)1.9%
Missing473732
Missing (%)40.6%
Memory size8.9 MiB
Documentary
137983 
Drama
108864 
Comedy
59900 
Animation
 
32120
Music
 
25824
Other values (13502)
329524 

Length

Max length173
Median length144
Mean length11.936881
Min length3

Unique

Unique7904 ?
Unique (%)1.1%

Sample

1st rowAction, Science Fiction, Adventure
2nd rowAdventure, Drama, Science Fiction
3rd rowDrama, Action, Crime, Thriller
4th rowAction, Adventure, Fantasy, Science Fiction
5th rowScience Fiction, Action, Adventure

Common Values

ValueCountFrequency (%)
Documentary 137983
 
11.8%
Drama 108864
 
9.3%
Comedy 59900
 
5.1%
Animation 32120
 
2.8%
Music 25824
 
2.2%
Horror 22960
 
2.0%
Drama, Romance 10748
 
0.9%
Comedy, Drama 9646
 
0.8%
Action 7973
 
0.7%
Romance 7870
 
0.7%
Other values (13497) 270327
23.1%
(Missing) 473732
40.6%

Length

2025-02-02T17:28:31.102781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama 229615
21.0%
documentary 168091
15.4%
comedy 141278
12.9%
animation 58449
 
5.3%
horror 54585
 
5.0%
romance 53614
 
4.9%
music 49645
 
4.5%
thriller 47345
 
4.3%
action 44854
 
4.1%
crime 33912
 
3.1%
Other values (10) 212522
19.4%

production_companies
Categorical

High cardinality  Missing 

List of production companies involved in the movie

Distinct209322
Distinct (%)39.9%
Missing643803
Missing (%)55.1%
Memory size8.9 MiB
Evil Angel
 
2952
ONF | NFB
 
2256
BBC
 
2151
Metro-Goldwyn-Mayer
 
2044
Columbia Pictures
 
1937
Other values (209317)
512804 

Length

Max length708
Median length423
Mean length24.523829
Min length1

Unique

Unique167678 ?
Unique (%)32.0%

Sample

1st rowLegendary Pictures, Syncopy, Warner Bros. Pictures
2nd rowLegendary Pictures, Syncopy, Lynda Obst Productions
3rd rowDC Comics, Legendary Pictures, Syncopy, Isobel Griffiths, Warner Bros. Pictures
4th rowDune Entertainment, Lightstorm Entertainment, 20th Century Fox, Ingenious Media
5th rowMarvel Studios

Common Values

ValueCountFrequency (%)
Evil Angel 2952
 
0.3%
ONF | NFB 2256
 
0.2%
BBC 2151
 
0.2%
Metro-Goldwyn-Mayer 2044
 
0.2%
Columbia Pictures 1937
 
0.2%
Toei Company 1788
 
0.2%
Nikkatsu Corporation 1634
 
0.1%
Universal Pictures 1548
 
0.1%
Paramount 1510
 
0.1%
Warner Bros. Pictures 1501
 
0.1%
Other values (209312) 504823
43.2%
(Missing) 643803
55.1%

Length

2025-02-02T17:28:31.284575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
productions 75932
 
4.7%
films 75859
 
4.7%
film 64040
 
4.0%
pictures 47151
 
2.9%
entertainment 34449
 
2.1%
studios 19330
 
1.2%
media 15514
 
1.0%
company 15459
 
1.0%
production 13762
 
0.9%
studio 13499
 
0.8%
Other values (101233) 1239339
76.8%

production_countries
Categorical

High cardinality  Imbalance  Missing 

List of countries involved in the movie production

Distinct10166
Distinct (%)1.6%
Missing523518
Missing (%)44.8%
Memory size8.9 MiB
United States of America
181180 
Japan
41360 
United Kingdom
34420 
Germany
33265 
France
33224 
Other values (10161)
320980 

Length

Max length3023
Median length333
Mean length13.562084
Min length4

Unique

Unique7016 ?
Unique (%)1.1%

Sample

1st rowUnited Kingdom, United States of America
2nd rowUnited Kingdom, United States of America
3rd rowUnited Kingdom, United States of America
4th rowUnited States of America, United Kingdom
5th rowUnited States of America

Common Values

ValueCountFrequency (%)
United States of America 181180
 
15.5%
Japan 41360
 
3.5%
United Kingdom 34420
 
2.9%
Germany 33265
 
2.8%
France 33224
 
2.8%
India 20556
 
1.8%
Canada 19500
 
1.7%
Brazil 16411
 
1.4%
Italy 13581
 
1.2%
Spain 11742
 
1.0%
Other values (10156) 239190
20.5%
(Missing) 523518
44.8%

Length

2025-02-02T17:28:31.443871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united 238371
20.1%
states 196086
16.5%
america 196076
16.5%
france 45379
 
3.8%
germany 43885
 
3.7%
japan 43073
 
3.6%
kingdom 41933
 
3.5%
canada 24702
 
2.1%
india 21444
 
1.8%
italy 19061
 
1.6%
Other values (282) 315022
26.6%

spoken_languages
Categorical

High cardinality  Imbalance  Missing 

List of languages spoken in the movie

Distinct7106
Distinct (%)1.1%
Missing503846
Missing (%)43.1%
Memory size8.9 MiB
English
237622 
Japanese
40656 
Spanish
37712 
French
37091 
No Language
29536 
Other values (7101)
281484 

Length

Max length177
Median length7
Mean length8.1805057
Min length3

Unique

Unique4731 ?
Unique (%)0.7%

Sample

1st rowEnglish, French, Japanese, Swahili
2nd rowEnglish
3rd rowEnglish, Mandarin
4th rowEnglish, Spanish
5th rowEnglish, Hindi, Russian

Common Values

ValueCountFrequency (%)
English 237622
20.3%
Japanese 40656
 
3.5%
Spanish 37712
 
3.2%
French 37091
 
3.2%
No Language 29536
 
2.5%
German 28712
 
2.5%
Portuguese 19068
 
1.6%
Russian 17022
 
1.5%
Mandarin 16040
 
1.4%
Italian 15209
 
1.3%
Other values (7096) 185433
 
15.9%
(Missing) 503846
43.1%

Length

2025-02-02T17:28:31.616075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 276206
37.4%
french 50186
 
6.8%
spanish 46898
 
6.3%
japanese 44157
 
6.0%
german 38466
 
5.2%
language 30286
 
4.1%
portuguese 21711
 
2.9%
russian 21643
 
2.9%
italian 20448
 
2.8%
mandarin 19513
 
2.6%
Other values (179) 169363
22.9%

keywords
Text

Missing 

Keywords associated with the movie

Distinct179343
Distinct (%)57.4%
Missing855292
Missing (%)73.2%
Memory size8.9 MiB
2025-02-02T17:28:32.234014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1588
Median length738
Mean length37.550393
Min length1

Unique

Unique165788 ?
Unique (%)53.0%

Sample

1st rowrescue, mission, dream, airplane, paris, france, virtual reality, kidnapping, philosophy, spy, allegory, manipulation, car crash, heist, memory, architecture, los angeles, california, dream world, subconscious
2nd rowrescue, future, spacecraft, race against time, artificial intelligence (a.i.), nasa, time warp, dystopia, expedition, space travel, wormhole, famine, black hole, quantum mechanics, family relationships, space, robot, astronaut, scientist, single father, farmer, space station, curious, space adventure, time paradox, thoughtful, time-manipulation, father daughter relationship, 2060s, cornfield, time manipulation, complicated
3rd rowjoker, sadism, chaos, secret identity, crime fighter, superhero, anti hero, scarecrow, based on comic, vigilante, organized crime, tragic hero, anti villain, criminal mastermind, district attorney, super power, super villain, neo-noir
4th rowfuture, society, culture clash, space travel, space war, space colony, tribe, romance, alien, futuristic, space, alien planet, marine, soldier, battle, love affair, nature, anti war, power relations, joyful
5th rownew york city, superhero, shield, based on comic, alien invasion, superhero team, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
ValueCountFrequency (%)
film 43281
 
3.0%
short 29485
 
2.0%
woman 20550
 
1.4%
gay 18409
 
1.3%
director 16304
 
1.1%
sex 15770
 
1.1%
based 15483
 
1.1%
pornography 11921
 
0.8%
relationship 10728
 
0.7%
comedy 9087
 
0.6%
Other values (36997) 1257414
86.8%
2025-02-02T17:28:32.912004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-02-02T17:27:51.091569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:37.576170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:39.689925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:41.922446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:44.108679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:46.252221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:51.400140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:37.958545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:40.008123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:42.272471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:44.413055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:46.543243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:51.703572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:38.312276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:40.364174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:42.658476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:44.735475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:46.839164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:51.997212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:38.662637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:40.744027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:43.018510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:45.105032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:50.065270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:52.293361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:39.012346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:41.119061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:43.396137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:45.534449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:50.402192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:52.573273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:39.369553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:41.525472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:43.783604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:45.931163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-02T17:27:50.725384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Missing values

2025-02-02T17:27:56.040587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Sample

idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords
027205Inception8.36434495Released2010-07-15825532764148False/8ZTVqvKDQ8emSGUEMjsS4yHAwrp.jpg160000000https://www.warnerbros.com/movies/inceptiontt1375666enInceptionCobb, a skilled thief who commits corporate espionage by infiltrating the subconscious of his targets is offered a chance to regain his old life as payment for a task considered to be impossible: "inception", the implantation of another person's idea into a target's subconscious.83.952/oYuLEt3zVCKq57qu2F8dT7NIa6f.jpgYour mind is the scene of the crime.Action, Science Fiction, AdventureLegendary Pictures, Syncopy, Warner Bros. PicturesUnited Kingdom, United States of AmericaEnglish, French, Japanese, Swahilirescue, mission, dream, airplane, paris, france, virtual reality, kidnapping, philosophy, spy, allegory, manipulation, car crash, heist, memory, architecture, los angeles, california, dream world, subconscious
1157336Interstellar8.41732571Released2014-11-05701729206169False/pbrkL804c8yAv3zBZR4QPEafpAR.jpg165000000http://www.interstellarmovie.net/tt0816692enInterstellarThe adventures of a group of explorers who make use of a newly discovered wormhole to surpass the limitations on human space travel and conquer the vast distances involved in an interstellar voyage.140.241/gEU2QniE6E77NI6lCU6MxlNBvIx.jpgMankind was born on Earth. It was never meant to die here.Adventure, Drama, Science FictionLegendary Pictures, Syncopy, Lynda Obst ProductionsUnited Kingdom, United States of AmericaEnglishrescue, future, spacecraft, race against time, artificial intelligence (a.i.), nasa, time warp, dystopia, expedition, space travel, wormhole, famine, black hole, quantum mechanics, family relationships, space, robot, astronaut, scientist, single father, farmer, space station, curious, space adventure, time paradox, thoughtful, time-manipulation, father daughter relationship, 2060s, cornfield, time manipulation, complicated
2155The Dark Knight8.51230619Released2008-07-161004558444152False/nMKdUUepR0i5zn0y1T4CsSB5chy.jpg185000000https://www.warnerbros.com/movies/dark-knight/tt0468569enThe Dark KnightBatman raises the stakes in his war on crime. With the help of Lt. Jim Gordon and District Attorney Harvey Dent, Batman sets out to dismantle the remaining criminal organizations that plague the streets. The partnership proves to be effective, but they soon find themselves prey to a reign of chaos unleashed by a rising criminal mastermind known to the terrified citizens of Gotham as the Joker.130.643/qJ2tW6WMUDux911r6m7haRef0WH.jpgWelcome to a world without rules.Drama, Action, Crime, ThrillerDC Comics, Legendary Pictures, Syncopy, Isobel Griffiths, Warner Bros. PicturesUnited Kingdom, United States of AmericaEnglish, Mandarinjoker, sadism, chaos, secret identity, crime fighter, superhero, anti hero, scarecrow, based on comic, vigilante, organized crime, tragic hero, anti villain, criminal mastermind, district attorney, super power, super villain, neo-noir
319995Avatar7.57329815Released2009-12-152923706026162False/vL5LR6WdxWPjLPFRLe133jXWsh5.jpg237000000https://www.avatar.com/movies/avatartt0499549enAvatarIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.79.932/kyeqWdyUXW608qlYkRqosgbbJyK.jpgEnter the world of Pandora.Action, Adventure, Fantasy, Science FictionDune Entertainment, Lightstorm Entertainment, 20th Century Fox, Ingenious MediaUnited States of America, United KingdomEnglish, Spanishfuture, society, culture clash, space travel, space war, space colony, tribe, romance, alien, futuristic, space, alien planet, marine, soldier, battle, love affair, nature, anti war, power relations, joyful
424428The Avengers7.71029166Released2012-04-251518815515143False/9BBTo63ANSmhC4e6r62OJFuK2GL.jpg220000000https://www.marvel.com/movies/the-avengerstt0848228enThe AvengersWhen an unexpected enemy emerges and threatens global safety and security, Nick Fury, director of the international peacekeeping agency known as S.H.I.E.L.D., finds himself in need of a team to pull the world back from the brink of disaster. Spanning the globe, a daring recruitment effort begins!98.082/RYMX2wcKCBAr24UyPD7xwmjaTn.jpgSome assembly required.Science Fiction, Action, AdventureMarvel StudiosUnited States of AmericaEnglish, Hindi, Russiannew york city, superhero, shield, based on comic, alien invasion, superhero team, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
5293660Deadpool7.60628894Released2016-02-09783100000108False/en971MEXui9diirXlogOrPKmsEn.jpg58000000https://www.20thcenturystudios.com/movies/deadpooltt1431045enDeadpoolThe origin story of former Special Forces operative turned mercenary Wade Wilson, who, after being subjected to a rogue experiment that leaves him with accelerated healing powers, adopts the alter ego Deadpool. Armed with his new abilities and a dark, twisted sense of humor, Deadpool hunts down the man who nearly destroyed his life.72.735/zq8Cl3PNIDGU3iWNRoc5nEZ6pCe.jpgWitness the beginning of a happy ending.Action, Adventure, Comedy20th Century Fox, The Donners' Company, Genre FilmsUnited States of AmericaEnglishsuperhero, anti hero, mercenary, based on comic, aftercreditsstinger, duringcreditsstinger
6299536Avengers: Infinity War8.25527713Released2018-04-252052415039149False/mDfJG3LC3Dqb67AZ52x3Z0jU0uB.jpg300000000https://www.marvel.com/movies/avengers-infinity-wartt4154756enAvengers: Infinity WarAs the Avengers and their allies have continued to protect the world from threats too large for any one hero to handle, a new danger has emerged from the cosmic shadows: Thanos. A despot of intergalactic infamy, his goal is to collect all six Infinity Stones, artifacts of unimaginable power, and use them to inflict his twisted will on all of reality. Everything the Avengers have fought for has led up to this moment - the fate of Earth and existence itself has never been more uncertain.154.340/7WsyChQLEftFiDOVTGkv3hFpyyt.jpgAn entire universe. Once and for all.Adventure, Action, Science FictionMarvel StudiosUnited States of AmericaEnglish, Xhosasacrifice, magic, superhero, based on comic, space, battlefield, genocide, magical object, super power, aftercreditsstinger, marvel cinematic universe (mcu), cosmic
7550Fight Club8.43827238Released1999-10-15100853753139False/hZkgoQYus5vegHoetLkCJzb17zJ.jpg63000000http://www.foxmovies.com/movies/fight-clubtt0137523enFight ClubA ticking-time-bomb insomniac and a slippery soap salesman channel primal male aggression into a shocking new form of therapy. Their concept catches on, with underground "fight clubs" forming in every town, until an eccentric gets in the way and ignites an out-of-control spiral toward oblivion.69.498/pB8BM7pdSp6B6Ih7QZ4DrQ3PmJK.jpgMischief. Mayhem. Soap.DramaRegency Enterprises, Fox 2000 Pictures, Taurus Film, Atman Entertainment, Knickerbocker Films, The Linson Company, 20th Century FoxUnited States of AmericaEnglishdual identity, rage and hate, based on novel or book, nihilism, fight, support group, dystopia, insomnia, alter ego, breaking the fourth wall, split personality, quitting a job, dissociative identity disorder, self destructiveness
8118340Guardians of the Galaxy7.90626638Released2014-07-30772776600121False/uLtVbjvS1O7gXL8lUOwsFOH4man.jpg170000000http://marvel.com/guardianstt2015381enGuardians of the GalaxyLight years from Earth, 26 years after being abducted, Peter Quill finds himself the prime target of a manhunt after discovering an orb wanted by Ronan the Accuser.33.255/r7vmZjiyZw9rpJMQJdXpjgiCOk9.jpgAll heroes start somewhere.Action, Science Fiction, AdventureMarvel StudiosUnited States of AmericaEnglishspacecraft, based on comic, space, orphan, adventurer, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
9680Pulp Fiction8.48825893Released1994-09-10213900000154False/suaEOtk1N1sgg2MTM7oZd2cfVp3.jpg8500000https://www.miramax.com/movie/pulp-fiction/tt0110912enPulp FictionA burger-loving hit man, his philosophical partner, a drug-addled gangster's moll and a washed-up boxer converge in this sprawling, comedic crime caper. Their adventures unfurl in three stories that ingeniously trip back and forth in time.74.862/d5iIlFn5s0ImszYzBPb8JPIfbXD.jpgJust because you are a character doesn't mean you have character.Thriller, CrimeMiramax, A Band Apart, Jersey FilmsUnited States of AmericaEnglish, Spanish, Frenchdrug dealer, boxer, massage, stolen money, briefcase, crime boss, redemption, heirloom, dance competition, los angeles, california, theft, nonlinear timeline, multiple storylines, neo-noir, hilarious
idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords
1167937792595Undone0.00ReleasedNaN08FalseNaN0https://collab.sundance.org/catalog/Undone-2020-03-16-143009NaNenUndoneAfter cutting all their hair off and getting caught gender bending, Amelia must navigate a day at school. Seeking for support they eventually find solace in their friends. Sundance Ignite 20210.6/lhrkJFNkRfdTpviLGPQubw15Jdr.jpgNaNNaNNaNNaNNaNsundance ignite
1167938792596Extended Perspective, Taking Steps Back0.00Released2021-02-0102FalseNaN0NaNNaNenExtended Perspective, Taking Steps BackWe move out; More and more enter the frame.0.6/qU2cz3vGYG9kBfbsBs6nTHvtg8B.jpgNaNNaNNaNNaNNaNNaN
11679397925971.3.60.00Released2004-12-31041FalseNaN0NaNNaNko1.3.6NaN0.6NaNNaNNaNNaNSouth KoreaKoreanNaN
1167940276217The Cure: Rock Case Studies0.00Released2007-01-0100FalseNaN0NaNNaNenThe Cure: Rock Case StudiesMusic &amp; Musicals, Rockumentaries, Rock &amp; Pop, Modern &amp; Alternative Rock - Featuring performance footage and commentary from musicians, fans and critics, this in-depth analysis of alternative rock band the Cure examines the influence of the unique group that came of age in the post-punk era and continues to draw fans today. A rare archival interview with lead singer Robert Smith sheds light on the Cure's music and history, and footage of the band's performance on British show "The Tube" provides a special treat.0.6NaNNaNNaNNaNNaNNaNNaN
1167941792600La intemperie sin fin0.00Released1977-10-09044FalseNaN0NaNNaNesLa intemperie sin finThe film “Documentary Experience N ° 3 - Juan L. Ortiz” (Endless Weathering) constitutes an investigative work on one of the greatest Argentine poets.0.6/AaH4zwdoMsaT98dVmjYxrLZdXdj.jpgNaNDocumentaryNaNArgentinaNaNNaN
1167942792601Cidade de Bebedouro - Est. de São Paulo0.00Released1911-01-0100FalseNaN0NaNNaNptCidade de Bebedouro - Est. de São PauloNaN0.6NaNNaNNaNNaNBrazilNaNNaN
1167943792602Los Boys0.00Released2012-07-08082FalseNaN0NaNNaNesLos BoysIf breakdance was a dance of cultural resistance of the Afro community in the US, perhaps this documentary shows a continuity with the northern Argentine adolescence. The Boys Street is a breakdancing group recognized through their presentations on the reality television show Talento Argentino, where they reached the final. Its members are adolescents between 12 and 18 years old from Palpalá, a town in the southeast of the province of Jujuy. Without technical knowledge, the group recorded the process of participating in the program with their own video cameras, crudely portraying their experience as a counterpart to the formality and aestheticization of reality. Los Boys recovers the history of the group at the same time that it captures the daily life of its members in the present day of Palpalá, a town that was recognized as "Mother of Industry" since it had several industrial parks, but was systematically dismantled after the coup d'état and during the privatizations of the '90s.0.6/oiPjoYA0x7et43MT0e4Zod2NKCd.jpgNaNDocumentaryNaNArgentinaNaNNaN
1167944792604But What Was She Wearing?0.00Released2018-11-030110FalseNaN0NaNtt10073458enBut What Was She Wearing?In 1992, Bhanwari Devi, an Indian social worker hailing from the Kumhar caste in rural Rajasthan, was gang-raped by upper caste men for having the temerity to intervene and stop the child-marriage of an infant. The subsequent acquittal of the accused in connivance with the state machinery outraged India and galvanized women’s activism that led to the Vishaka Guidelines, and subsequently the Sexual Harassment of Women at Workplace Act in 2013. This documentary juxtaposes the law on paper with the ground realities, through a first-of-its-kind log of stories and experiences of over two dozen Indian women; tales of sexual violence that they face - from opulent corporate offices, to construction sites and manual scavenging - and their fight for justice against an obstinate patriarchal state. ‘But What Was She Wearing?’ attempts to portray the impotence of this paper-law and the impossible odds Indian women are up against in pursuit of justice.0.6/dmu5rOn1PMOjK5HzkXU8X8Tfuil.jpgA film on workplace sexual harassment — policies vs reality.DocumentaryLime Soda FilmsIndiaEnglish, Hindi, Malayalam, TamilNaN
1167945276216The Chick Corea Elektric Band: Live at the Maintenance Shop0.00Released1985-10-30075False/mpBclSCRvjyiPTrBsrisqdmiRon.jpg0NaNNaNenThe Chick Corea Elektric Band: Live at the Maintenance ShopMusic & Musicals, Jazz Greats, Classic Jazz, Jazz & Easy Listening - Groundbreaking keyboardist Chick Corea takes the stage at Iowa State University with bassist John Patitucci and drummer Dave Weckl to perform a rousing set of songs of electric jazz fusion, a genre Corea helped define during the 1960s. This 1985 concert showcases the trio's wizardry on tunes such as "King Cockroach," "Malaguena," "Rumble," "India Town" and "Sidewalk." This program also features a biography of the band.0.6/mT9le0OFkrTzcPg0orXJT5P3dXT.jpgNaNMusicNaNNaNEnglishNaN
11679461423447Thomas & Friends: Daisy and Other Thomas Stories0.00Released1993-10-06036FalseNaN0NaNNaNenThomas & Friends: Daisy and Other Thomas StoriesPEEP-PEEP! Come Journey to the Island of Sodor and share in the fun-filled escapades of Thomas the Tank Engine and Friends. Meet Daisy, a "classy sassy passenger diesel," as well as Trevor, the very useful tractor engine. You'll see why Percy's up to his funnel in water, Gordon looks foolish, and Henry is proud, in their adventures through the Island of Sodor. So join the gang on Sir Topham Hatt's Railway line in Thomas the Tank Engine and Friends Volume 9.0.6/9sTnj6l3aWiDLwyznWC4mBMo87y.jpgNaNNaNNaNNaNNaNNaN

Duplicate rows

Most frequently occurring

idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords# duplicates
321192957Soldiers From Eastern Europe 130.00Released2005-10-120114TrueNaN0NaNNaNenSoldiers From Eastern Europe 13Another combat training session gone suck-cessful! Join Eastern Euro-soldiers as they hit the training facilities for more hardcore sexual man-action!0.0/3miaWnx10YRplzPW3CDOjC1MGoE.jpgNaNNaNEagle VideoCzech RepublicNaNNaN4
551199214Last Laughs0.00Released2023-05-28047FalseNaN0NaNNaNenLast LaughsFarewell the Comedy Festival for another year in one glorious night out at SkyCity Theatre! Grab your comedy-loving mates and be a part of the magic as we announce the winners of the prestigious Billy T and Fred Awards, and celebrate the very best of the Fest - all in one show.     Hosted by Chris Parker and featuring headliner Michèle A'Court.0.0NaNNaNNaNNaNNaNEnglishNaN4
761205264Hopeless: The Film0.00Released2023-09-30052TrueNaN0NaNNaNenHopeless: The FilmHopeless stars Casey Calvert and Lumi Ray as best friends whose relationship metamorphoses into something unexpected - and extraordinary - when a devastated Casey turns to Lumi for comfort after a painful breakup.0.0NaNNaNRomanceHolly Randall ProductionsNaNNaNlesbian relationship4
811206572Dude, Don't Fuck My Wife 30.00Released2014-12-150143TrueNaN0NaNNaNenDude, Don't Fuck My Wife 3C'mon man, leave my wife alone! The husbands beg and beg but dudes won't stop fucking their wives. It's a shame. These powerless cuckolds can do nothing but watch as hung lovers and side pieces fuck their wives well right before their very eyes. The wives are unhappy until they get more cock in their pussy. These husbands can't bear to watch but they just can't stop looking.0.0/336ojave64saSsHKwakJorbH72u.jpgNaNNaNNaughty SinnerUnited States of AmericaNaNNaN4
1121213633My Sister Is Wet & Horny0.00Released2014-10-060100TrueNaN0NaNNaNenMy Sister Is Wet & HornyA family that lays together stays together! They aren't so little anymore! They've grown up to be so sweet, so wet, so horny and willing to do whatever it takes to keep that big dick in the family! When Isabella De Santos got a look at Ralph's dick pic on twitter she couldn't wait to see how many licks it takes to get every last gooey drop out of his monster cock! Tony came home from college for summer and found Kacey living in his bedroom, they are going to have to share, and guess what? There will be no bunk beds this time! Sandra didn't want Brad to tell everybody from the Old Country about her pussy pies.0.0/jCxYKTIDfYEQJNZ4xcFxgJmJo80.jpgNaNNaNLethal HardcoreNaNNaNNaN4
1451221745Last Day0.00ReleasedNaN038TrueNaN0NaNNaNenLast Dayno description yet ...0.0NaNNaNNaNNaNNaNNaNNaN4
1621224655Don't Break Me 390.00ReleasedNaN0155TrueNaN0NaNNaNenDon't Break Me 39Jackie Hoff gets fucked hard by J-Mac. Hot Latina Maya Farrel graves J-Mac's hard dick. Rachel Starr loves fucking more than anything. Petite Payton Avery takes on J-Mac's thick dick. Catalina Ossa gets her trimmed pussy pounded.0.0/35FuFb0B1WzaE80gYKcpJen4b5G.jpgNaNNaNNaNNaNNaNNaN4
1631224661Mr. Roberts0.00ReleasedNaN033FalseNaN0NaNNaNenMr. RobertsIn "Mr. Roberts", written by Terrence McNally and staring Jonathan Taylor Thomas and Steven Weber, a teacher in a 1970's classroom struggles with his closeted gay status and a student who is on the verge of coming out of the closet.0.0NaNNaNNaNNaNNaNNaNNaN4
2061235259Gogo no Kouchou: Junai Mellow yori0.00Released2012-09-21030TrueNaN0NaNNaNja午後の紅潮 ~純愛メロウより~NaN0.0NaNNaNAnimationNaNJapanJapanesehentai4
2251240115My Pretty Cospet 20.00Released2004-01-0100TrueNaN0NaNNaNesMy Pretty Cospet 2NaN0.0/3FkkHtybRMfsOJxzYyc4M3GLPQ3.jpgNaNNaNNaNJapanNaNNaN4